Role of mass spectrometry in the diagnostics and therapeutics
Understanding disease pathology has been made easier with the advent of various mass spectrometry techniques. This complex instrument is operated on the principle of the separation of the fragment ions of a complex molecule(s) based on their mass to charge ratio (m/z) and identification of these ions from known sequence database samples. Simultaneous identification and quantification of proteins, bioactive compounds, small molecules including various drugs, steroid hormones and adulterations is possible with ultrahigh accuracy. Additionally, mass spectrometry can be efficiently used to study complex proteomes, biomarker discovery, protein post translational modifications analysis, and protein-protein interaction studies.
A mass spectrometer consists of:
· Inlet system (LC, GC, Direct probe etc...)
· Ion source (EI, CI, ESI, APCI, MALDI, etc...)
· Mass analyzer (Quadrupole, Time of Flight (TOF), Ion Trap, Magnetic Sector)
· Detector (Electron Multiplier, Micro Channel Plates MCPs) (1)
A digested peptide (small number of amino acids), or small molecules to be analyzed, are extracted from the source in a suitable solvent. The amount of sample required for analysis is very small, in the range of nanograms to micrograms. These samples are loaded onto a high-performance liquid chromatography (HPLC) system wherein the detector is a mass spectrometer, hence the term LC-MS. The peptides are fractionated in the HPLC based on their hydrophobicity, chirality, net size, net charge, etc. depending on the column utilized. In practice, the sample is loaded onto the HPLC, and the components are separated and eluted from the column with an appropriate solvent gradient. There are a variety of available analyzers including but not necessarily limited to quadrupole, c-trap, Orbitrap™, matrix assisted laser desorption ionization (MALDI), etc. Ionization sources include electro spray ionization, collision induced dissociation, high energy collision induced dissociation, atmospheric pressure chemical ionization etc. (1). Sample ions are converted to the gaseous phase by several of the ionization mechanisms available in the mass analyzer. These fragments carry multiple charges, which are separated based on their mass to charge ratio. The current generated is converted to an output signal by the detector.
There are several types of mass spectrometers available depending upon the type of ionization source and mass analyzers used. The software available with these different mass spectrometers are designed to perform specialized functions. For example, complex proteome identification and quantification as well as post translational modification analysis can be effectively performed on Orbitrap™, Triple TOF®, Synapt™ mass spectrometers. Identification of small molecules is done on triple quadrupole. The raw output data from the LC-MS is in the form of mass spectra. There are several data analysis interfaces available which are specific to the instrument being utilized. For example, the output data file from thermo Orbitrap Velos™ is .RAW, which is visualized on Excalibur™, while data analysis is done on the Proteome Discoverer™ software. The data obtained from triple TOF is in .wiff format and could be analyzed on ProteinPilot™ software. The protein sequence databases Uniprot™, Human Refseq, contain proteins with known peptide sequences from various sources. The spectral data, utilizing appropriate software, is matched against these databases. Utilizing a high-resolution mass spectrometer, identification of a large number of proteins is possible. Complex biological problems including disease pathology, biomarker identification, temporal changes in a system, etc. can be addressed more simply utilizing mass spectrometry as well as other analytical tools.
(Image credit: technologynetworks.com)
Examples of use of mass spectrometry to understand diseases: PCOS (body fluid):
Polycystic ovary syndrome (PCOS) a complex disorder and one of the major causes of anovulatory infertility (9-18% prevalence in reproductive age women) is manifested by hormonal imbalance (raised Luteinizing hormone: Follicle Stimulating Hormone ‘LH: FSH’), hyperandrogenemia, acne, alopecia, hirsutism, hyperinsulinemia, insulin resistance, anovulation, and polycystic ovaries on ultrasound (2). However, the etiology of follicular growth arrest in PCOS is not clear. In an attempt to understand aberrant folliculogenesis in these afflicted women, Ambekar et al. studied normal follicular fluid proteome and its alteration in PCOS using high-resolution mass spectrometry (3, 4). Follicular fluid is a constituent of the periovulatory follicle which surrounds the developing oocyte and influences its developmental and fertilization acquisition competence. Follicular fluid proteome has been studied in order to understand the pathology of various reproductive disorders: recurrent spontaneous abortion, ovarian hyper stimulation syndrome, endometriosis, etc.
Authors employed a high-resolution mass spectrometry based proteomic approach for in-depth proteomic analysis of normal follicular fluid. Follicular fluid was collected from women undergoing in vitro fertilization (IVF) during ovum “pick up” from women with PCOS and age matched healthy women undergoing IVF due to male factor infertility. For normal follicular fluid catalog study, an equal amount of protein was pooled from six different samples and to reduce sample complexity, high abundant proteins were depleted from follicular fluid using a multiple affinity removal system 14 column-HPLC. Flow through fraction proteome (low abundant proteins) was cataloged by deep fractionation of protein/ peptides using SDS PAGE, OFFGEL electrophoresis and strong cation exchange (SCX) chromatography coupled to high resolution LC-MS (LTQ Orbitrap Velos®). A total of 480 proteins were identified in follicular fluid with high confidence; of which 323 were novel in the follicular fluid and 19 were novel in the ovary at the time of publication. Proteins of complement coagulation cascade, extracellular matrix (ECM) proteins of follicular matrices, growth factors, immunity associated proteins, etc. were identified and the presence of lectin induced complement pathway constituents was detected for the first time in the follicular fluid (3). Absolute quantification (iTRAQ®) based quantitative proteomics approach was utilized to analyze proteomic alterations in the follicular fluid from PCOS, a 4-plex isobaric tag for relative. Each iTRAQ® reagent is made up of a unique charged reporter group, a peptide reactive group, and a neutral balance group which maintains an overall mass of 145Da. iTRAQ® tags are isobaric labels that react with primary amines of peptides including the N-terminus and ε-amino group of the lysine sidechain. Due to the isobaric mass design of the iTRAQ® reagents, differentially labeled peptides appear as a single peak in mass spectral (MS) scans. When iTRAQ®-tagged peptides are subjected to MS/ MS, the iTRAQ® reporter groups break off from the peptide, liberating the isotope encoded reporter ions and produce distinct ions at m/z 114, 115, 116 and 117. Relative intensities of the reporter ions are directly proportional to the relative abundances of each peptide in samples that are being compared. This methodology provides relative quantitative information on the proteins (4). An equal amount of protein was pooled from six control and six PCOS samples, processed separately for high abundant proteins depletion, trypsin digestion and iTRAQ® labeling. Labeled peptides were pooled and subjected to SCX and LC-MS/MS analysis. It identified 770 proteins, of which 186 were found to be altered in abundance in PCOS. These dysregulated proteins were involved in several processes of folliculogenesis e.g., metabolism, ECM remodeling, angiogenesis, complement activity, immune function, complement coagulation cascade etc. that are necessary for normal folliculogenesis indicating defect in these processes. This study suggests that the follicular growth arrest in PCOS could be a cumulative effect of the alteration of several processes as previously mentioned (5). Based on these proteomic findings, a study on the validation of dysregulated follicular angiogenesis in PCOS was carried out (6).
Pathology of cancer:
Understanding tissue specific pathology in various cancer types is necessary in order to identify drug targets which can be effectively used to control metastasis, recurrence or prevent cancer in susceptible individuals. Using conventional mass spectrometry several researchers have studied tissue specific pathology of various types of cancer (7). Breast cancer is one of the leading causes of mortality in women worldwide. Based on tumor receptors status, lymph node positivity and tumor grade there are five known breast cancer subtypes. These cancer subtypes are luminal A (ER+, HER2−, low proliferation), luminal B HER2−(ER+, HER2−, high proliferation), luminal B HER2+(ER+, HER2+, high proliferation), HER2 enriched (ER−, HER2+, high proliferation), and triple negative (ER−, PR−, HER2−, high proliferation). However, in many cases adjuvant therapy designed based on the conventional classification system fails to afford a complete cure.
In addition, therapy resistance develops indicating that classification may not cover the true genetic and molecular profile of breast cancer. To address this issue using proteomics, a targeted global proteomic approach of Sequential Window Acquisition of all Theoretical Fragment ion spectra (SWATH) coupled to mass spectrometry, was used to generate a breast cancer tissue proteome library from 96 tumor tissue samples. SWATH analysis is information dependent data acquisition where all fragment ions are considered in a series of specific mass range (sequential window). Hence more comprehensive analysis is possible in comparison to data dependent acquisition where ions in only a specific broad m/z range are subjected to MS/MS. Their proteomic based tumor subgroup classification and hierarchical clustering analysis of the proteomic findings is in accordance with the conventional classification system, however, their finding also revealed heterogeneity within these subtypes and triple negative breast cancer was the most heterogeneous among these. Proteins that contribute most strongly to the proteotype-based classification were INPP4B, CDK1, and ERBB2 and they were associated with estrogen receptor (ER) status, tumor grade status, and HER2 status (8). Heterogeneous and the constantly mutating nature of the tumor tissue makes it difficult to accurately identify cancer biomarkers/ drug targets.
A recently developed method of MALDI-imaging mass spectrometry which utilizes mapping of the ion image of the tumor sections and its comparison with the immunohistochemically stained sections of the same tissue, can help to unravel the spatial changes in the tumor microenvironment and identify tumor markers. MALDI-imaging mass spectrometry has been used in brain, breast, head and neck, skin, colon, pancreas, liver and cancers of the reproductive systems. Similarly molecular pathology of the brain disorders including Alzimer’s disease, Parkinson’s disease is difficult to study owing to unavailability of tissue samples. To overcome this limitation, MALDI-imaging has been principally used in the brain autopsy specimens of the patients or transgenic animal models (9).
SILAC based identification of drug targets:
Stable isotope labeled amino acid in cell culture (SILAC) based quantification is a metabolic labeling strategy, in which cells of the treatment group are grown in a medium containing amino acid stable isotopes of carbon/ nitrogen e.g. C13 arginine, which are incorporated in all cellular constituent proteins during growth and multiplication for multiple generations. At the same time, another treatment group is cultured in a normal medium with arginine containing a normal isotope of carbon. Number of tags present in a protein is proportional to the number of arginine amino acids. The heavy and light isotopes differ by 6 da, which is reflected in the MS/MS spectra. The differences in the protein and peptide abundance are calculated from MS/MS ion intensities. Thus by comparing light and heavy proteomes it is possible to compare the treated and control groups (10).
Antibiotic vancomycin is commonly used to treat neonatal staphylococcal sepsis. It is a drug of choice against methicilline resistant Staphylococci, Enterococcus faecalis etc. The pharmacokinetic response in neonates differs from adults, and this antibiotic is often responsible for nephrotoxicity. To determine the molecular targets of vancomycin cytotoxicity, (SILAC) and LC-MS proteomics was utilized by Ling et al. (11). Authors studied the effect of vancomycin on HK-2 kidney cell line using SILAC. They identified approximately 492 targets of vancomycin of which 178 proteins were upregulated and 314 were down regulated. Pathway analysis suggested that these proteins and pathways played a critical role in the regulation of cell cycle, apoptosis, autophagy, epithelial to mesenchymal transition, and reactive oxygen species generation. This data may be used to discriminate the molecular and clinical subtypes and to identify new targets and biomarkers for vancomycin-induced nephrotoxic effects.
Identification and quantification of clinically important small molecules, diagnostic fragment ions by selected reaction monitoring:
Owing to higher sensitivity, specificity, cost effectiveness and rapid detection ability compared to immune assays, mass spectrometry techniques are applied in the clinical diagnostics field where more accurate identification is required. Identification of the small molecules by mass spectrometry is preferred over immunoassays due to following advantages. Immune assay principally relies on the antibody-based identification of the molecule of interest where there are chances of cross reactivities and false positive identification. Mass spectrometry is more specific. Immune assays may not work properly for hemolyzed blood samples. In mass spectrometry, the molecule of interest is extracted by a suitable method prior to analysis, hence analysis can be performed in hemolyzed samples. It is rapid and less time consuming. The entire process can be completed within 4 hours, with a maximum of 10-12 min analysis time per sample. Samples can be analyzed on the same day of collection.
Diagnosis of bioactive compounds including various steroid and peptide hormones from patient blood samples is done using high resolution mass spectrometry in a clinical laboratory setup. For example, accurate estimation of the insulin concentration is essential for diagnosis of insulin resistance. Such determination is efficiently performed using mass spectrometry and certainly supports the immunoassays of ELISA and radioimmunoassay (RIA). As an example, insulin is extracted from the blood in a suitable solvent. Analysis and quantification of the intact insulin molecule or its characteristic fragment ions is possible. The methods used for this purpose are selected ion monitoring (SIM) and selected reaction monitoring (SRM) respectively (12, 13). Various concentrations of insulin standards are analyzed on mass spectrometer, in which sample is injected in HPLC column and with a standard gradient of solvents, column bound insulin is eluted and analyzed on a mass spectrometer in the SIM mode. During SRM analysis, a specific fragment ion of the insulin generated during MS/MS fragmentation is monitored. A standard graph of insulin concentration is plotted against the area under curve of intact insulin or insulin fragment ion m/z. Insulin concentration of the sample is extrapolated from this standard curve. These representative examples well illustrate the applications of mass spectrometry in disease diagnosis and treatment.
Written By: Aditi Ambekar, Ph.D. & Lawrence D. Jones, Ph.D.
1) Rolf Ekman, Jerzy Silberring, Ann Westman-Brinkmalm, Agnieszka Kraj. MASS SPECTROMETRY Instrumentation, Interpretation, and Applications WILEY-INTERSCIENCE SERIES IN MASS SPECTROMETRY (book chapter).
2) Balen AH, Morley LC, Misso M, Franks S, Legro RS, Wijeyaratne CN, Stener-Victorin E, Fauser BC, Norman RJ, Teede H. The management of anovulatory infertility in women with polycystic ovary syndrome: an analysis of the evidence to support the development of global WHO guidance. Hum Reprod Update. 2016; 22 (6):687-708.
3) Ambekar AS, Nirujogi RS, Srikanth SM, Chavan S, Kelkar DS, Hinduja I, Zaveri K, Prasad TS, Harsha HC, Pandey A, Mukherjee S. Proteomic analysis of human FF: a new perspective towards understanding folliculogenesis. J. Proteomics. 2013; 87:68-77.
4) Ambekar AS, Kelkar DS, Pinto SM, Sharma R, Hinduja I, Zaveri K, Pandey A, Prasad TSK, Gowda H, Mukherjee S. Proteomics of FF from Women with Polycystic Ovary Syndrome Suggests Molecular Defects in Follicular Development. J Clin Endocrinol Metab. 2015; 100:744-753.
5) Zieske, L.R. A perspective on the use of iTRAQ reagent technology for protein complex and profiling studies. J. Exp. Bot. 2006; 57: 1501-1508.
6) Krutika Patil, Indira Hinduja, Srabani Mukherjee. Alteration in angiogenic potential of granulosa-lutein cells and follicular fluid contributes to luteal defects in polycystic ovary syndrome. Hum Reprod. 2021; 36(4):1052-1064.
7) Pavel Bouchal, Olga T Schubert, Jakub Faktor, Lenka Capkova, Hana Imrichova, Karolina Zoufalova, Vendula Paralova, Roman Hrstka, Yansheng Liu, Holger Alexander Ebhardt, Eva Budinska, Rudolf Nenutil, Ruedi Aebersold. Breast Cancer Classification Based on Proteotypes Obtained by SWATH Mass Spectrometry. Cell Rep. 2019; 28(3):832-843.
8) Cristina Alexandra Ciocan-Cartita, Ancuța Jurj, Mihail Buse, Diana Gulei, Cornelia Braicu, Lajos Raduly, Roxana Cojocneanu, Lavinia Lorena Pruteanu, Cristina Adela Iuga, Ovidiu Coza, Ioana Berindan-Neagoe. The Relevance of Mass Spectrometry Analysis for Personalized Medicine through Its Successful Application in Cancer "Omics" Int J Mol Sci. 2019; 20(10):2576.
9) Yasemin Ucal, Zeynep Aslıhan Durer, Hakan Atak, Elif Kadioglu, Betul Sahin, Abdurrahman Coskun, Ahmet Tarık Baykal, Aysel Ozpinar. Clinical applications of MALDI imaging technologies in cancer and neurodegenerative diseases. Biochim Biophys Acta Proteins Proteom. 2017; 1865(7):795-816.
10) Shao-En Ong, Matthias Mann Stable isotope labeling by amino acids in cell culture for quantitative proteomics. Methods Mol Biol. 2007; 359:37-52.
11) Zhi-Ling Li and Shu-Feng ZhouA. SILAC-Based Approach Elicits the Proteomic Responses to Vancomycin-Associated Nephrotoxicity in Human Proximal Tubule Epithelial HK-2 Cells. Molecules. 2016; 21(2), 148.
12) S M Darby, M L Miller, R O Allen, M LeBeau. A mass spectrometric method for quantitation of intact insulin in blood samples. J Anal Toxicol. 2001; 25(1):8-14.
13) Zhaohui Chen, Michael P Caulfield, Michael J McPhaul, Richard E Reitz, Steven W Taylor, Nigel J Clarke. Quantitative insulin analysis using liquid chromatography-tandem mass spectrometry in a high-throughput clinical laboratory. Clin Chem. 2013; 59(9):1349-56.